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new 6a66908e09 [doc] fix url positioning in documents (#4630)
6a66908e09 is described below
commit 6a66908e0923de43b9c0dfa97c232bbac7ab3c92
Author: yangjf2019 <[email protected]>
AuthorDate: Wed Dec 4 11:36:29 2024 +0800
[doc] fix url positioning in documents (#4630)
---
docs/content/flink/sql-ddl.md | 4 ++--
docs/content/flink/sql-write.md | 2 +-
docs/content/spark/sql-ddl.md | 2 +-
3 files changed, 4 insertions(+), 4 deletions(-)
diff --git a/docs/content/flink/sql-ddl.md b/docs/content/flink/sql-ddl.md
index 8b8c069229..a373348861 100644
--- a/docs/content/flink/sql-ddl.md
+++ b/docs/content/flink/sql-ddl.md
@@ -101,7 +101,7 @@ Also, you can create [FlinkGenericCatalog]({{< ref
"flink/quick-start" >}}).
By default, Paimon does not synchronize newly created partitions into Hive
metastore. Users will see an unpartitioned table in Hive. Partition push-down
will be carried out by filter push-down instead.
-If you want to see a partitioned table in Hive and also synchronize newly
created partitions into Hive metastore, please set the table property
`metastore.partitioned-table` to true. Also see [CoreOptions]({{< ref
"maintenance/configurations#CoreOptions" >}}).
+If you want to see a partitioned table in Hive and also synchronize newly
created partitions into Hive metastore, please set the table property
`metastore.partitioned-table` to true. Also see [CoreOptions]({{< ref
"maintenance/configurations#coreoptions" >}}).
#### Adding Parameters to a Hive Table
@@ -114,7 +114,7 @@ For instance, using the option `hive.table.owner=Jon` will
automatically add the
If you are using an object storage , and you don't want that the location of
paimon table/database is accessed by the filesystem of hive,
which may lead to the error such as "No FileSystem for scheme: s3a".
You can set location in the properties of table/database by the config of
`location-in-properties`. See
-[setting the location of table/database in properties ]({{< ref
"maintenance/configurations#HiveCatalogOptions" >}})
+[setting the location of table/database in properties ]({{< ref
"maintenance/configurations#hivecatalogoptions" >}})
### Creating JDBC Catalog
diff --git a/docs/content/flink/sql-write.md b/docs/content/flink/sql-write.md
index 3b6a0498eb..60c0f5c36c 100644
--- a/docs/content/flink/sql-write.md
+++ b/docs/content/flink/sql-write.md
@@ -79,7 +79,7 @@ The data is clustered using an automatically chosen strategy
(such as ORDER, ZOR
by setting the `sink.clustering.strategy`. Clustering relies on sampling and
sorting. If the clustering process takes too much time, you can decrease
the total sample number by setting the `sink.clustering.sample-factor` or
disable the sorting step by setting the `sink.clustering.sort-in-cluster` to
false.
-You can refer to [FlinkConnectorOptions]({{< ref
"maintenance/configurations#FlinkConnectorOptions" >}}) for more info about the
configurations above.
+You can refer to [FlinkConnectorOptions]({{< ref
"maintenance/configurations#flinkconnectoroptions" >}}) for more info about the
configurations above.
## Overwriting the Whole Table
diff --git a/docs/content/spark/sql-ddl.md b/docs/content/spark/sql-ddl.md
index 3b4d1722bc..4a82d6b4a4 100644
--- a/docs/content/spark/sql-ddl.md
+++ b/docs/content/spark/sql-ddl.md
@@ -88,7 +88,7 @@ Also, you can create [SparkGenericCatalog]({{< ref
"spark/quick-start" >}}).
By default, Paimon does not synchronize newly created partitions into Hive
metastore. Users will see an unpartitioned table in Hive. Partition push-down
will be carried out by filter push-down instead.
-If you want to see a partitioned table in Hive and also synchronize newly
created partitions into Hive metastore, please set the table property
`metastore.partitioned-table` to true. Also see [CoreOptions]({{< ref
"maintenance/configurations#CoreOptions" >}}).
+If you want to see a partitioned table in Hive and also synchronize newly
created partitions into Hive metastore, please set the table property
`metastore.partitioned-table` to true. Also see [CoreOptions]({{< ref
"maintenance/configurations#coreoptions" >}}).
### Creating JDBC Catalog
